Experimental Study of a Hybrid Genetic Algorithm for the Multiple Travelling Salesman Problem

Maha Ata Al-Furhud and Zakir Hussain Ahmed

Mathematical Problems in Engineering, 2020, vol. 2020, 1-13

Abstract:

The multiple travelling salesman problem (MTSP), an extension of the well-known travelling salesman problem (TSP), is studied here. In MTSP, starting from a depot, multiple salesmen require to visit all cities so that each city is required to be visited only once by one salesman only. It is NP-hard and is more complex than the usual TSP. So, exact optimal solutions can be obtained for smaller sized problem instances only. For large-sized problem instances, it is essential to apply heuristic algorithms, and amongst them, genetic algorithm is identified to be successfully deal with such complex optimization problems. So, we propose a hybrid genetic algorithm (HGA) that uses sequential constructive crossover, a local search approach along with an immigration technique to find high-quality solution to the MTSP. Then our proposed HGA is compared against some state-of-the-art algorithms by solving some TSPLIB symmetric instances of several sizes with various number of salesmen. Our experimental investigation demonstrates that the HGA is one of the best algorithms.

Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:3431420

DOI: 10.1155/2020/3431420

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